CCUS and Geothermal Energy Activities in Saskatchewan, Canada: Novel Technologies in Carbon Capture and Storage Related the University of Regina's Clean Energy Technologies Research Institute and the PTRC's Aquistore Deep Saline Storage Project
Notice bibliographique
Résumé
Abstract The province of Saskatchewan in Canada has two of the largest CCUS projects in the world - the Weyburn CO2-EOR flood and the Aquistore Deep Saline CO2 Storage Project. Learnings from these operations have powered significant research in capture, storage, and (inadvertently) geothermal energy production. This work will examine how these commercial operations have fostered important research into solvents for less expensive capture technologies, and reservoir characterization and monitoring that has enhanced CO2 storage while simultaneously enhancing geothermal production. The 23-year history of CO2 EOR and deep saline storage in Saskatchewan has led to a material advantage for research groups in the province - both in the areas of CO2 capture research, and CO2 deep geological storage. The SaskPower Boundary Dam Capture Facility, and the Aquistore site have both facilitated R&D programs at Saskatchewan's universities and research organizations into reactive solvent capture technologies, and at PTRC in novel measurement, monitoring and verification tools. The accumulated data from those two industrial scale projects (capture and storage) have facilitated unique findings worth sharing with other planned CCS projects now in development. Over 30 different kinds of measurement, monitoring and verification technologies for storage have been examined and compared at the Aquistore Deep Saline Storage Project. The results on plume monitoring and surveillance, using both DAS and DTS (fibre optic) deployment has shown a surprising repeatability of results as compared to the site's permanent geophone array. Novel deep fluid sampling to examine brine-CO2 interactions, and ongoing extensive sometimes surprising data related to second-by-second injection at the wellhead has revealed salt precipitation and pressure data that is crucial for planned projects globally, particularly those that may experience stop-and-start injection regimes. In relation to reactive solvent development in the field of capture, CETRI (U of R) has developed a synergistic combination of novel solvent and catalytic packing in its facility that significantly reduces energy requirements and equipment size for CO2 capture, resulting in a lower cost process. This next generation capture technology provides decarbonization across many challenging applications and industrial sources. The research at CETRI, which has played an important role in the optimization of the Boundary Dam facility in the past, is building on that experience. Both the real-time data at Aquistore, and the catalyst-aided solvent development at the University of Regina draw from industrial scale CCUS in Saskatchewan. Interestingly, the saline formation characterization that informed Aquistore, has now provided crucial data for southern Saskatchewan about temperatures and fluid flow that is encouraging geothermal heating in cities like Regina and Estevan, offering insight into how research into emissions reduction technologies can help inform and expand additional low carbon projects.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».